Exploring SILO Patched Point Weather Stations¶

This notebook demonstrates how to search and visualize all available weather stations in the SILO Patched Point dataset. The resulting interactive map shows station locations colored by elevation and includes station numbers that can be used for data queries.

In [1]:

# ## Setup and Imports
import geopandas as gpd

from weather_tools.silo_api import SiloAPI

# ## Setup and Imports import geopandas as gpd from weather_tools.silo_api import SiloAPI

Search for All SILO Weather Stations¶

The search_stations() method with the wildcard pattern "__" returns metadata for all available stations in the SILO Patched Point dataset. This includes:

• Station codes (used for data queries)
• Geographic coordinates (latitude/longitude)
• Elevation above sea level
• Station names and other metadata

In [2]:

silo_api = SiloAPI(log_level="INFO")
station_meta = silo_api.search_stations("__")

# Convert to GeoDataFrame for spatial operations and mapping
gdf = gpd.GeoDataFrame(
    station_meta,
    geometry=gpd.points_from_xy(station_meta.longitude, station_meta.latitude),
    crs=4326,
)

print(f"Found {len(gdf)} weather stations in SILO database")

silo_api = SiloAPI(log_level="INFO") station_meta = silo_api.search_stations("__") # Convert to GeoDataFrame for spatial operations and mapping gdf = gpd.GeoDataFrame( station_meta, geometry=gpd.points_from_xy(station_meta.longitude, station_meta.latitude), crs=4326, ) print(f"Found {len(gdf)} weather stations in SILO database")

Found 7995 weather stations in SILO database

Interactive Station Map¶

This map displays all SILO weather stations colored by elevation (meters above sea level). Map Features:

• Color scale: Lower elevations (coastal) appear green, higher elevations (mountains) appear brown
• Click any marker to view station details including the station code
• Use station codes from the popup to query weather data via the CLI or API Example Query Using Station Code:

weather-tools silo patched-point --station 30043 \
 --start-date 20230101 --end-date 20231231 --var R --var X

In [3]:

gdf.explore(
    "elevation",  # use elevation column for color
    cmap="terrain",
    marker_kwds=dict(radius=5, stroke=False, alpha=0.8),
)

gdf.explore( "elevation", # use elevation column for color cmap="terrain", marker_kwds=dict(radius=5, stroke=False, alpha=0.8), )

Out[3]:

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